Improve dataset card: Consolidate metadata, add links, sample usage, and citation

README.md

@@ -1,17 +1,3 @@
-# Active Perception AAWR Dataset in GRASP Lab Mock Kitchen 
-
-Here is our full dataset (13.5GB) in DROID format:
-https://huggingface.co/datasets/Everloom/AAWR-DROID/ 
-
-It includes 4 scene as below, each are cleaned with a white list (filter the idle frames)
-
-![image](https://cdn-uploads.huggingface.co/production/uploads/649939137e4bb2372ef88394/pE_hJnP6lmC0J5VPWHCFj.png)
-
-Here is a website on searching behavior under 3rd camera view
-https://sites.google.com/view/rwrl-ap/home
-
-Please comment below with you suggestions , which will be very helpful for our release!
-
 ---
 license: mit
 task_categories:
@@ -23,5 +9,62 @@ tags:
 - robotics
 - RL
 size_categories:
-- 100M<n<1B
----
+- 10B<n<100B
+---
+
+# Active Perception AAWR Dataset in GRASP Lab Mock Kitchen
+
+[Paper](https://huggingface.co/papers/2512.01188) | [Project page](https://penn-pal-lab.github.io/aawr/) | [Code](https://github.com/penn-pal-lab/aawr)
+
+Here is our full dataset (13.5GB) in DROID format:
+https://huggingface.co/datasets/Everloom/AAWR-DROID/
+
+It includes 4 scene as below, each are cleaned with a white list (filter the idle frames)
+
+![image](https://cdn-uploads.huggingface.co/production/uploads/649939137e4bb2372ef88394/pE_hJnP6lmC0J5VPWHCFj.png)
+
+## Sample Usage
+
+To get started with AAWR, follow these steps for a toy simulated task, as described in the [code repository](https://github.com/penn-pal-lab/aawr):
+
+### Setup
+
+1.  **Install Python dependencies**: You can refer to the `environment.yaml` file, or just manually install the dependencies. There's not too many, mainly `torch`, `gymnasium` and their related packages.
+
+2.  **Install the simulated xarm environment code, and generate demos**:
+    ```bash
+    git@github.com:edwhu/gym-xarm.git
+    pip install -e .
+    python generate_demos.py # generate demo data.
+
+    mkdir gymnasium_xarm_lift_bc
+    mv buffer.pkl gymnasium_xarm_lift_bc
+    ```
+
+### Train AAWR
+
+Train AAWR on a simple simulated lifting task:
+
+```bash
+python src/train_il.py agent=asym_awr modality=all task=gymnasium_xarm_lift dataset_dir=data/gymnasium_xarm_lift_bc seed=41 use_wandb=false exp_name=aawr_xarm_lift horizon=1 offline_steps=20000 train_steps=40000 lr=1e-4 grad_clip_norm=10 awr_filter=indicator expectile=0.9 A_scaling=3 save_video=true switch_awr_filter=true
+```
+
+## Citation
+
+If you find our project helpful, please cite us:
+
+```bibtex
+@inproceedings{
+    hu2025realworld,
+    title={Real-World Reinforcement Learning of Active Perception Behaviors},
+    author={Edward S. Hu and Jie Wang and Xingfang Yuan and Fiona Luo and Muyao Li and Gaspard Lambrechts and Oleh Rybkin and Dinesh Jayaraman},
+    booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
+    year={2025},
+    url={https://openreview.net/forum?id=RkdTtznSAL}
+}
+```
+
+## Additional Resources
+
+Here is a website on searching behavior under 3rd camera view:
+https://sites.google.com/view/rwrl-ap/home